Hollow-tree super: A directional and scalable approach for feature importance in boosted tree models.
<h4>Purpose</h4>Current limitations in methodologies used throughout machine-learning to investigate feature importance in boosted tree modelling prevent the effective scaling to datasets with a large number of features, particularly when one is investigating both the magnitude and direc...
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| Auteurs principaux: | , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Public Library of Science (PLoS)
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/8f5e5821182e4f03bbf2bbd5ff7ed511 |
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